Working Paper: CEPR ID: DP10792
Authors: Dirk Bergemann; Benjamin Brooks; Stephen Morris
Abstract: This paper explores the consequences of information in sealed bid first price auctions. For a given symmetric and arbitrarily correlated prior distribution over valuations, we characterize the set of possible outcomes that can arise in a Bayesian equilibrium for some information structure. In particular, we characterize maximum and minimum revenue across all information structures when bidders may not know their own values, and maximum revenue when they do know their values. Revenue is maximized when buyers know who has the highest valuation, but the highest valuation buyer has partial information about others? values. Revenue is minimized when buyers are uncertain about whether they will win or lose and incentive constraints are binding for all upward bid deviations. We provide further analytic results on possible welfare outcomes and report computational methods which work when we do not have analytic solutions. Many of our results generalize to asymmetric value distributions. We apply these results to study how entry fees and reserve prices impact the welfare bounds.
Keywords: Bayes; Correlated Equilibrium; Common Values; First Price Auctions; Information Structure; Interdependent Values; Private Values; Revenue; Welfare Bounds
JEL Codes: C72; D44; D82; D83
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| knowledge of relative valuations (D46) | revenue maximized (H21) |
| uncertainty about winning chances (D81) | revenue minimized (H29) |
| bidders do not know their own values (D44) | revenue significantly lower (H27) |